Using computer vision and neural networks for defect detection in manufacturing

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dc.contributor.authorSotnychenko, Viktor
dc.date.accessioned2025-10-19T12:00:18Z
dc.date.issued2025
dc.description.abstractThe research explores the application of computer vision and neural networks for automated defect detection in manufacturing processes. Deep learning-based algorithms analyze visual data to identify defects, optimize quality control, and enhance production efficiency [1]. The study aims to reduce human error, increase detection accuracy, and minimize production losses.
dc.identifier.citationSotnychenko V. Using computer vision and neural networks for defect detection in manufacturing [Electronic resours] / Viktor Sotnychenko ; research supervisor Igor Yakovenko ; lang. support supervisor Tetyana Sergeyeva // An Innovative Model of Research Projects Aimed at the Integration of Ukraine into the European Scientific Space : book of abstr. an Annual Intern. PhD Conf., April 24, 2025 / National Technical University "Kharkiv Polytechnic Institute". – Electronic text data. – Kharkiv : NTU "KhPI", 2025. – P. 250-252.
dc.identifier.urihttps://repository.kpi.kharkov.ua/handle/KhPI-Press/94191
dc.language.isoen
dc.publisherNational Technical University "Kharkiv Polytechnic Institute"
dc.subjectcomputer vision
dc.subjectneural networks
dc.subjectdefect detection
dc.subjectdeep learning
dc.subjectautomation
dc.subjectmanufacturing quality control
dc.titleUsing computer vision and neural networks for defect detection in manufacturing
dc.typeArticle

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An Innovative Model of Research Projects Aimed at the Integration of Ukraine into the European Scientific Space. 2025